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DBMS > Apache Druid vs. CrateDB vs. GeoMesa vs. HBase

System Properties Comparison Apache Druid vs. CrateDB vs. GeoMesa vs. HBase

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonCrateDB  Xexclude from comparisonGeoMesa  Xexclude from comparisonHBase  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataDistributed Database based on LuceneGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Wide-column store based on Apache Hadoop and on concepts of BigTable
Primary database modelRelational DBMS
Time Series DBMS
Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Spatial DBMSWide column store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#10  Vector DBMS
Score0.86
Rank#205  Overall
#4  Spatial DBMS
Score27.97
Rank#26  Overall
#2  Wide column stores
Websitedruid.apache.orgcratedb.comwww.geomesa.orghbase.apache.org
Technical documentationdruid.apache.org/­docs/­latest/­designcratedb.com/­docswww.geomesa.org/­documentation/­stable/­user/­index.htmlhbase.apache.org/­book.html
DeveloperApache Software Foundation and contributorsCrateCCRi and othersApache Software Foundation infoApache top-level project, originally developed by Powerset
Initial release2012201320142008
Current release29.0.1, April 20245.0.0, May 20242.3.4, January 2021
License infoCommercial or Open SourceOpen Source infoApache license v2Open SourceOpen Source infoApache License 2.0Open Source infoApache version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaScalaJava
Server operating systemsLinux
OS X
Unix
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux
Unix
Windows infousing Cygwin
Data schemeyes infoschema-less columns are supportedFlexible Schema (defined schema, partial schema, schema free)yesschema-free, schema definition possible
Typing infopredefined data types such as float or dateyesyesyesoptions to bring your own types, AVRO
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nononono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL for queryingyes, but no triggers and constraints, and PostgreSQL compatibilitynono
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
C
C#
C++
Groovy
Java
PHP
Python
Scala
Server-side scripts infoStored proceduresnouser defined functions (Javascript)noyes infoCoprocessors in Java
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingdepending on storage layerSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesConfigurable replication on table/partition-leveldepending on storage layerMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Read-after-write consistency on record level
depending on storage layerImmediate Consistency or Eventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infounique row identifiers can be used for implementing an optimistic concurrency control strategynoSingle row ACID (across millions of columns)
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonodepending on storage layeryes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemrights management via user accountsyes infodepending on the DBMS used for storageAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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Apache DruidCrateDBGeoMesaHBase
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